AIMC Topic: Epilepsy, Temporal Lobe
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Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.
NeuroImage. Clinical
Sep 28, 2017
OBJECTIVE: To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patterns estimated during EEG periods without visible pathological activity.
Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 22, 2017
Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal epileptiform discharge (IED) detection, have traditionally employed handcrafted features, which utilized specific characteristics of neural responses. A...
Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.
Brain and language
Sep 9, 2017
Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks ...
Machine learning classification of mesial temporal sclerosis in epilepsy patients.
Epilepsy research
Sep 9, 2015
BACKGROUND AND PURPOSE: Novel approaches applying machine-learning methods to neuroimaging data seek to develop individualized measures that will aid in the diagnosis and treatment of brain-based disorders such as temporal lobe epilepsy (TLE). Using ...
Machine Learning of DTI Structural Brain Connectomes for Lateralization of Temporal Lobe Epilepsy.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Sep 4, 2015
BACKGROUND AND PURPOSE: We analyzed the ability of a machine learning approach that uses diffusion tensor imaging (DTI) structural connectomes to determine lateralization of epileptogenicity in temporal lobe epilepsy (TLE).
Diffusion Tensor Imaging
Frontal Lobe
Temporal Lobe
Globus Pallidus
Nucleus Accumbens
Hippocampus
Connectome
Gyrus Cinguli
Epilepsy, Temporal Lobe
Occipital Lobe
Brain
Retrospective Studies
Female
Young Adult
Adult
Male
Middle Aged
Case-Control Studies
Imaging, Three-Dimensional
Support Vector Machine
Humans
Machine Learning
Multimodal data and machine learning for surgery outcome prediction in complicated cases of mesial temporal lobe epilepsy.
Computers in biology and medicine
Jun 19, 2015
BACKGROUND: This study sought to predict postsurgical seizure freedom from pre-operative diagnostic test results and clinical information using a rapid automated approach, based on supervised learning methods in patients with drug-resistant focal sei...
Evaluation of machine learning algorithms for treatment outcome prediction in patients with epilepsy based on structural connectome data.
NeuroImage
Jun 6, 2015
The objective of this study is to evaluate machine learning algorithms aimed at predicting surgical treatment outcomes in groups of patients with temporal lobe epilepsy (TLE) using only the structural brain connectome. Specifically, the brain connect...
Impaired dendritic inhibition leads to epileptic activity in a computer model of CA3.
Hippocampus
Apr 22, 2015
Temporal lobe epilepsy (TLE) is a common type of epilepsy with hippocampus as the usual site of origin. The CA3 subfield of hippocampus is reported to have a low epileptic threshold and hence initiates the disorder in patients with TLE. This study co...
Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 21, 2014
The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe epilepsy (TLE) is a challenging task. In many cases, patients with a record of epileptic activity do not present any discernible MRI findings. In this...
Redefining diagnostic lesional status in temporal lobe epilepsy with artificial intelligence.
Brain : a journal of neurology
Jun 3, 2025
Despite decades of advancements in diagnostic MRI, 30%-50% of temporal lobe epilepsy (TLE) patients remain categorized as 'non-lesional' (i.e. MRI negative) based on visual assessment by human experts. MRI-negative patients face diagnostic uncertaint...
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